skill-python-research
Research Python/Z3 patterns and APIs for semantic theory development. Invoke for Python-language research tasks.
发现 数据与 AI 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。
Research Python/Z3 patterns and APIs for semantic theory development. Invoke for Python-language research tasks.
Atomically update task status across TODO.md and state.json. Invoke when task status changes.
Create phased implementation plans from research findings. Invoke when a task needs an implementation plan.
Execute general implementation tasks following a plan. Invoke for non-Lean implementation work.
Create scoped git commits for task operations. Invoke after task status changes or artifact creation.
Обновление README.md по текущему состоянию кода и метрик тестирования (make test, make infection), с синхронизацией docs/ARCHITECTURE.md при архитектурных изменениях.
This skill should be used when teams need to adopt Supertester to build deterministic Elixir OTP tests with isolation, synchronization, and supervision coverage.
AI面试教练,提供全面的面试准备、模拟和反馈。覆盖技术面试、系统设计、行为面试(STAR法则)、HR面试。生成面试题、模拟真实面试、提供详细反馈和改进建议。当用户准备面试或进行模拟面试时自动触发。
职业发展顾问。分析技能差距、推荐学习路径、规划职业发展、指导角色转换。帮助你做出战略性的职业决策。
优化和定制简历以匹配特定公司和职位。分析JD,提取关键技能,重新排序经验,突出相关成就。用于创建简历变体、优化关键词、提升ATS通过率。当用户创建简历变体或优化简历时自动触发。
分析职位描述(JD)以提取关键信息、技能要求、资格条件。识别核心技能、软技能、经验要求。用于简历匹配、面试准备、技能差距分析。当用户提供JD文本或添加公司信息时自动触发。
智能协调器,编排多个技能和命令完成端到端的工作流。自动规划和执行复杂的多步骤任务。
LinkedIn职位导入器。解析LinkedIn职位发布,提取JD和公司信息,批量导入求职系统。
智能面试问题生成器。基于JD分析、用户简历和公司特点,生成定制化面试问题。支持技术面试、系统设计、行为面试(STAR)、HR面试。提供不同难度级别(简单/中等/困难)。自动维护问题库,追踪练习历史。与jd-analyzer和intervi...
薪资谈判专家。分析Offer、进行市场调研、生成谈判策略、起草还盘、对比多个Offer。帮助你获得最优薪资package。
通用 iOS App 开发、构建、签名、测试与 App Store 上架流程(中国区)指南。用于当用户询问 iOS 开发/上架/审核/签名/TestFlight/App Store Connect/隐私合规/订阅配置,或输入触发词 iosdev 时。
Advanced td_interval patterns including offset dates (-1d/2025-10-01, -7d/-1d, 0M/now), td_interval_range for debugging, td_time_string for display formatting, and partition pruning optimization.
Build LLM agents using `tdx agent pull/push` with YAML/Markdown config. Covers agent.yml structure, tools (knowledge_base, agent, web_search, image_gen), @ref syntax, and knowledge bases. Use for TD AI agent de...
Comprehensive template and guidelines for documenting Field Agents including technical specifications, system prompts, tool specifications, user interactions, and standardized documentation structure
TD Hive SQL with TD-specific functions and Hive-only features (lateral view, explode, MAPJOIN hint). Use when Trino memory errors occur or for Hive-specific syntax.
Expert documentation generation for staging transformation layers. Auto-detects SQL engine (Presto/Trino vs Hive), documents transformation rules, PII handling, deduplication strategies, and data quality rules....
Validates CDP journey YAML configurations against tdx schema requirements. Use when reviewing journey structure, checking step types and parameters, verifying segment references, or troubleshooting journey conf...
TD MCP server setup for Claude Code integration. Covers installation, regional configuration (us01, jp01, eu01), available tools (query, list_databases, describe_table), and write mode.
Best practices for developing, testing, and deploying production-ready Field Agents including R&D workflows, version control, testing strategies, and release management
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。